工作流程
药物开发
协变量
临床试验
多学科方法
样本量测定
计算机科学
随机对照试验
数据科学
医学
统计
药品
药理学
机器学习
数据库
内科学
社会学
社会科学
数学
作者
Konstantinos Sechidis,Sophie Sun,Yao Chen,Jiarui Lu,Cong Zhang,Mark Baillie,David Ohlssen,Marc Vandemeulebroecke,Rob Hemmings,Stephen J. Ruberg,Björn Bornkamp
摘要
ABSTRACT This article proposes a Workflow for Assessing Treatment effeCt Heterogeneity (WATCH) in clinical drug development targeted at clinical trial sponsors. WATCH is designed to address the challenges of investigating treatment effect heterogeneity (TEH) in randomized clinical trials, where sample size and multiplicity limit the reliability of findings. The proposed workflow includes four steps: analysis planning, initial data analysis and analysis dataset creation, TEH exploration, and multidisciplinary assessment. The workflow offers a general overview of how treatment effects vary by baseline covariates in the observed data and guides the interpretation of the observed findings based on external evidence and the best scientific understanding. The workflow is exploratory and not inferential/confirmatory in nature but should be preplanned before database lock and analysis start. It is focused on providing a general overview rather than a single specific finding or subgroup with a differential effect.
科研通智能强力驱动
Strongly Powered by AbleSci AI